According to the Department of Defense’s Chief Digital and AI Office, more than 2 million users accessed GenAI.mil in a single week, a dramatic increase from the roughly 80,000 AI users across DOD before the platform launched. GenAI.mil now provides secure access to government versions of Gemini, ChatGPT, and Grok for unclassified work, helping personnel analyze information, draft content, and streamline workflows. [nextgov.com]
One of the most interesting takeaways is not just AI usage, but AI creation. Within weeks of launching an agent-building capability, users created tens of thousands of custom AI agents to automate routine tasks and improve productivity.
For government leaders, this reinforces an important lesson:
- Adoption increases when AI tools are accessible, secure, and mission-focused.
- Employees embrace AI faster when it solves everyday workflow challenges.
- The future is not just using AI assistants, but empowering teams to build AI-powered solutions themselves.
As federal agencies continue their AI journey, the conversation is shifting from whether to adopt AI to how quickly organizations can scale it responsibly and securely.
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The jump from 80k to 2M users proves that when security barriers are removed, demand is already there waiting. But the real game-changer here is the bottom-up creation—tens of thousands of custom agents built by end users. Empowering non-technical teams to build their own workflow automation is how federal agencies will actually scale AI, rather than waiting on top-down IT deployments for every single use case.
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That shift from top-down software distribution to bottom-up user agency is massive for GovCon and federal spaces.
When you give subject-matter experts, the folks actually dealing with administrative bottlenecks every day, a secure sandbox to build their own targeted mini-agents, you eliminate months of IT scoping, procurement cycles, and rigid requirements gathering. It turns workflow automation into an emergent behavior rather than a scheduled project.
The main challenge now will be governance at scale: making sure agencies don’t end up with thousands of redundant, unmonitored shadow-agents while still preserving the low-friction creativity that made people adopt them in the first place.
The most compelling metric here isn’t raw usage — it’s the creation of tens of thousands of custom agents. When you give domain experts the ability to build no-code automation tailored to their specific niche, adoption moves from passive reading to active problem-solving. This shift from ‘AI consumer’ to ‘AI builder’ is the real blueprint for enterprise transformation.
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